Corpus ID: 6405271

SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents

@inproceedings{Nallapati2017SummaRuNNerAR,
  title={SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents},
  author={Ramesh Nallapati and Feifei Zhai and Bowen Zhou},
  booktitle={AAAI},
  year={2017}
}
We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art. Our model has the additional advantage of being very interpretable, since it allows visualization of its predictions broken up by abstract features such as information content, salience and novelty. Another novel contribution of our work is abstractive training of our extractive model that can… Expand
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  • Laifu Chen, M. Nguyen
  • Computer Science
  • 2019 11th International Conference on Knowledge and Systems Engineering (KSE)
  • 2019
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